What is threat modeling?

What is threat modeling?

Threat modeling is a structured process for identifying potential security threats to a system, understanding how an attacker might exploit them, and deciding what to do about them — ideally during design, before any vulnerable code is written.

A widely used framing reduces threat modeling to four questions:

• •What are we building? (model the system)
• •What can go wrong? (identify threats)
• •What are we going to do about it? (decide on mitigations)
• •Did we do a good enough job? (validate)

For a short definition, see the glossary entry for threat modeling.

Why threat modeling matters

Security flaws are cheapest to fix when they're caught in design. Threat modeling shifts security "left" — into the design and coding phases — so issues are addressed before they become incidents. The payoff:

• ✓Find design-level flaws that scanners and tests miss
• ✓Reduce the cost and risk of fixing issues after release
• ✓Build a shared understanding of the system's attack surface
• ✓Support secure-by-design requirements and compliance

The threat modeling process

Most threat modeling follows the same broad steps, regardless of methodology:

1. 1Model the system. Map components, data flows, and where data crosses trust boundaries — often as a data flow diagram.
2. 2Identify threats. Systematically enumerate what could go wrong, using a framework such as STRIDE or PASTA.
3. 3Assess and prioritize. Rate threats by likelihood and impact so the most serious are addressed first.
4. 4Mitigate. Decide on countermeasures — fix, reduce, transfer, or accept each risk.
5. 5Validate. Confirm mitigations are in place and revisit the model as the system changes.

Threat modeling methodologies

Methodologies give the "what can go wrong?" step structure. The most common:

• •STRIDE — A six-category framework for classifying technical threats. Fast and developer-friendly.
• •PASTA — A seven-stage, risk-centric methodology that ties threats to business impact.
• •DREAD — A model for scoring and ranking threats by severity.
• •LINDDUN — A methodology focused specifically on privacy threats.
• •Attack trees — Diagrams that model the paths an attacker could take to a goal.

The two most common are often compared directly — see STRIDE vs PASTA.

Core concepts

A few ideas show up in almost every threat model:

• •Data flow diagrams — Maps of how data moves through a system — the canvas threats are reasoned about on.
• •Trust boundaries — Points where the level of trust changes and data should be validated.
• •Attack surface — The total set of points where an attacker could interact with the system.

When and how often to threat model

Traditionally, threat modeling happens once, during design review. But systems change constantly, and every change can introduce new attack surface. The best practice is to threat-model whenever the system changes in a way that affects security — which, for most teams, means continuously.

That cadence is hard to hit by hand, which is why continuous threat modeling has emerged as the modern standard.

Threat modeling in DevSecOps

In a DevSecOps workflow, security is a shared responsibility built into the pipeline rather than a final gate. Threat modeling fits this model when it's automated and shifted left — running as part of how code is designed, built, and shipped. See CI/CD threat modeling.

Why traditional threat modeling doesn't scale

Manual threat modeling is thorough but slow. It depends on scarce security experts, requires diagrams to be drawn and maintained by hand, and can't realistically run on every change. The result is that models go stale, security becomes a bottleneck, and many changes ship without ever being analyzed.

The future: automated & continuous threat modeling

Automation closes the gap. With automated threat modeling, software — increasingly agentic AI — detects changes, runs STRIDE and PASTA, and delivers prioritized findings without manual effort. That makes it practical to threat-model continuously, keeping security in sync with development.

This is exactly what Virantis does: an agentic AI engine that watches your code, tickets, and docs across your stack and threat-models every change automatically.